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All Journal Jurnal Penelitian dan Evaluasi Pendidikan Jurnal Ilmu Sosial dan Ilmu Politik Jurnal Matematika Sains dan Teknologi Jurnal Organisasi Dan Manajemen Communications in Science and Technology Jurnal Ketenagakerjaan JUSTIN (Jurnal Sistem dan Teknologi Informasi) Prosiding Seminar Nasional Official Statistics PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Indonesian Journal of Statistics and Its Applications Jurnal Ekonomi Kependudukan dan Keluarga
Agung Priyo Utomo
Sekolah Tinggi Ilmu Statistik
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Determinan Perilaku Swamedikasi Penduduk Jawa Tengah Utomo, Agung Priyo; Syahida, Inayati; Berliana, Sarni Maniar; Samosir, Omas Bulan; Sugiarto, Sugiarto
Jurnal Ekonomi Kependudukan dan Keluarga Vol. 2, No. 1
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Self-medication has been practiced globally for thousands of years. As a part of primary healthcare services, self-medication forms the cornerstone of a sustainable healthcare system supporting universal health coverage, which is targeted in Sustainable Development Goal 3 (SDG 3), target 3.8. This study aims to provide an overview of self-medication behaviors and the factors influencing them among residents of Central Java Province. Using data from the 2021 National Socio-Economic Survey provided by the BPS-Statistics Indonesia, the sample size of this study includes 19,998 individuals, with 82.1% engaging in self-medication. The prevalence of self-medication is higher among males (84.0%) compared to females (80.6%). Self-medication is more common among individuals who are employed, live in rural areas, are unmarried, do not have health insurance, use the internet, are not poor, or have health complaints that do not interfere with daily activities, compared to their corresponding counterparts. The proportion of self-medication decreases with increasing age or higher education levels. Further binary logistic regression analysis identifies that the propensity for self-medication is higher among males (OR=1.16; 95% CI: 1.07-1.26), employed individuals (OR=1.40; 95% CI: 1.30-1.52), unmarried individuals (OR=1.17; 95% CI: 1.07-1.28), those without health insurance (OR=1.32; 95% CI: 1.20-1.44), the poor (OR=1.16; 95% CI: 1.02-1.31), those with health complaints that do not disrupt daily activities (OR=1.54; 95% CI: 1.43-1.66). The government needs to provide education and information regarding safe and responsible self-medication practices to at-risk groups, such as those with lower education levels, those without health insurance, and the poor, to maximize the benefits of self-medication and minimize the negative impacts of self-medication behaviors.
The Influence of Village Funds, HDI, GRDP, and Unemployment on Poverty in Sulawesi 2017-2024 Using Panel Data Regression Ramadhani, Muhammad Reza; Utomo, Agung Priyo
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.499

Abstract

Poverty in Indonesia remains a significant problem. Generally, rural poverty is higher than urban poverty. Therefore, the government has enacted a village fund policy through. Law Number 6 of 2024 to assist development efforts that can reduce rural poverty. However, despite a decline in national poverty, the poverty rate in Sulawesi has fluctuated. In addition to village funds, other variables influence poverty, such as human development index (HDI), gross regional domestic product (GRDP) per capita, and unemployment rate. The purpose of this study is to determine the effect of village funds, HDI, GRDP per capita, and unemployment on poverty rates in 70 districts in Sulawesi from 2017 to 2024. Data used are sourced from directorate general of fiscal balance (DJPK) for village funds and BPS for other variables. Panel data regression analysis is used to identify variables that influence poverty rates. Based on FEM, it is known that HDI and GRDP per capita have a negative and significant effect on poverty rates in Sulawesi Island. Village funds are insignificant in reducing poverty due to differences in development levels across regions. Therefore, equitable development and incre
Peramalan Harga Minyak Goreng Sawit di Indonesia: Perbandingan Model ARIMAX-GARCH, SVR, dan LSTM Yulianto, Mukhamad Dinda Manis; Utomo, Agung Priyo
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 14, No 2 (2026)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v14i2.97766

Abstract

Fluktuasi harga minyak goreng sawit sebagai komoditas pangan strategis memiliki dampak langsung terhadap inflasi dan stabilitas ekonomi rumah tangga di Indonesia. Meskipun berbagai penelitian telah mengembangkan model peramalan harga berbasis statistik konvensional maupun machine learning, sebagian besar masih membandingkan metode dalam pendekatan yang sama serta jarang mengintegrasikan indikator permintaan berbasis big data. Penelitian ini menawarkan kontribusi baru dengan membandingkan secara langsung pendekatan statistik konvensional ARIMAX–GARCH dan metode machine learning, yaitu Support Vector Regression (SVR) dan Long Short-Term Memory (LSTM), dalam meramalkan harga minyak goreng sawit kemasan di Indonesia, dengan memasukkan Indeks Google Trends sebagai proksi sisi permintaan. Hasil evaluasi menunjukkan bahwa model ARIMAX(2,1,2)–GARCH(1,1) menghasilkan kinerja terbaik dengan RMSE sebesar 1.274,29 dan MAPE 4,89%, dibandingkan dengan model SVR dan LSTM. Keunggulan model ini terletak pada kemampuannya dalam memodelkan heteroskedastisitas dan fenomena volatility clustering yang umum terjadi pada data harga pangan, sehingga menghasilkan estimasi titik dan interval peramalan yang lebih andal. Model terpilih memproyeksikan harga minyak goreng sawit cenderung menurun secara bertahap dari Rp21.692 pada Januari 2025 menjadi sekitar Rp20.988 pada Desember 2025. Hasil penelitian ini dapat dimanfaatkan oleh Kementerian Perdagangan sebagai komponen utama dalam pengembangan sistem peringatan dini harga minyak goreng sawit, dengan memanfaatkan interval kepercayaan sebagai sinyal awal untuk mempertimbangkan intervensi pasar, seperti operasi pasar atau kebijakan Domestic Market Obligation (DMO), guna menjaga stabilitas harga dan ketersediaan pasokan domestik.
MODELLING THE NUMBER OF NEW PULMONARY TUBERCULOSIS CASES WITH GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION METHOD Mumtaz, Tsuraya; Utomo, Agung Priyo
Indonesian Journal of Statistics and Applications Vol 2 No 2 (2018)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v2i2.175

Abstract

Tuberculosis (TB) is an infectious disease caused by Mycobacterium Tuberculosis. Untill now, TB is still one of the main problems in many countries, especially developing countries. Indonesia ranked second as the country with the highest TB cases in the world in 2015, where most cases were found in Java. This study was conducted to model the number of new pulmonary TB cases in Java by considering the spatial aspects using Geographically Weighted Negative Binomial Regression (GWNBR). GWNBR method was chosen because the data used in this study are overdispered. The result showed that the population density and percentage of healty homes were not significantly influential in each region. While the number of puskesmas, the percentage of smokers, the percentage of good PHBS, the percentage of diabetes mellitus, and the percentage of less IMT were significant in some regions. In general, the GWNBR model was better for modelling the number of new pulmonary TB cases than negative binomial regression and GWPR.
Co-Authors Abdul Karim Bahrul Hayat, Bahrul Farihah, Raisa Gabriela, Patrisia Januardi, Ryan Willmanda Mumtaz, Tsuraya Putra, Muhammad Dwirifqi Kharisma Ramadhani, Muhammad Reza Rini Rahani Samosir, Omas Bulan Saputro, Agung Eddy Suryo Sarni Maniar Berliana, Sarni Maniar Sugiarto S Syahida, Inayati Umar, Jahja Yulianto, Mukhamad Dinda Manis